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Concerning the problem of noise interference in the mechanical equipment fault signal acquisition, a novel mechanical equipment fault diagnosis method of wavelet shrinkage threshold based on Bayesian estimation combined with EMD is proposed. The fault signal denoising characteristics of different scales are considered in the proposed method. A new threshold which is suitable for the situation of noise...
Predicting microblog user retweet behaviors is the basis of building the information diffusion model in microblog social networks. In order to improve the accuracy of predicting user retweet behaviors, under the MRF (Markov Random Field) framework, the paper comprehensively analyzes the effects on user retweet behaviors caused by various features (e.g., user attributes and microblog contents) and...
Extracting opinion words and opinion targets from online reviews is an important task for fine-grained opinion mining. Usually, traditional extraction methods under the pipeline-based framework have higher precision but lower recall, while methods in the propagation-based framework possess greater recall but poorer precision. To achieve better performance both in precision and recall, this paper proposes...
While e-commerce has grown substantially over last several years, more and more people are utilizing this popular channel to purchase products and services. Thus the ability to predict user demographics, including gender, age and location has important applications in advertising, personalization, and recommendation. In this paper, we aim to automatically predict the users' genders based on their...
In order to improve the discriminant power, a new discriminant analysis algorithm is proposed based on Fisher's linear discriminant, called variant fisher discriminant analysis with orthogonal discriminant components (VFDAODC). The basic idea of the proposed VFDAODC is to overcome the problems of the conventional fisher discriminant analysis algorithm. First, a two-step feature extraction procedure...
We present a novel hierarchical MRFs optimization method for dense and deformable motion extraction in dynamic scenes. In particular, this hierarchical MRFs structure consists of two layers, the segmentation and the correspondence layer. Firstly, dynamic RGB-D foreground data is segmented through a pixel-level MRF in the segmentation layer. Subsequently, the extracted foreground data is transformed...
An approach for keyframe extraction using AdaBoost is proposed which is based on foreground detection. The aim of this approach is to extract keyframes from sequences of specific vehicle images of lane vehicle surveillance video. This method utilizes integral channel features and the area feature as the image feature descriptor, combined with training an AdaBoost classifier. The experimental results...
Extracting main object from photos is prerequisite for image processing and semantic image understanding in many areas especially in multimedia signal processing at internet. So far, either human interaction in single image or sequence image frames are required for the extraction and most of them still rely on hand-crafted features. In contrast, the proposed work cast the human boundary detection...
In this paper, the framework of MapReduce is explored for large-scale multimedia data mining. Firstly, a brief overview of MapReduce and Hadoop is presented to speed up large-scale multimedia data mining. Then, the high-level theory and low-level implementation for several key computer vision technologies involved in this work are introduced, such as 2D/3D interest point detection, clustering, bag...
In the management of the online public opinion and Internet intelligent information, people need to obtain the content of the forum threads for further research on the topic emotion and the dissemination of forum topics. This paper presents a method based on templates to extract web forum contents. Proposed method overcomes the problem which caused by the change of the web pages structures and contents,...
Support Vector Machines are an effective form of binary-class classification algorithm. To enhance the utilization of text structural features for information extraction, which are greatly restricted by the Hidden Markov Model (HMM), this paper proposes a support vector machine multi-class classification based on Markov properties to extract the information from a citation database. The proposed model...
To relieve "News Information Overload", classification, summarization and recommendation techniques have been proposed. However, these techniques fail to provide sufficient semantic information about news events. In this paper, considering5W1H (Who, What, Whom, When, Where and How), the full list of elements of a news article, we propose a novel approach to extract event semantic elements...
Analysis the positive and negative sentiments about each topic of the product are very useful to the customers and manufacturers. In this paper we propose a new topic sentiment mixture model which we call Semi-supervised Co-LDA model to obtain the positive and negative opinions from the reviews about each product. The Semi-supervised Co-LDA can model the topic and sentiment of the product reviews...
The purpose of this paper was to find some feature pattern which may be used in diagnosis of blood stasis syndrome (BSS, a unique concept of traditional Chinese medicine) with myocardial ischemia. After establishing an animal model of Chinese experimental miniature swine, 7 indicators in plasma, e.g. troponin T (cTNT), heat shock protein 27 (HSP27), cytochrome C (Cyt C), endothelin-1 (ET-1), calcitonin...
Unstable angina (UA) is a most dangerous type of Coronary Heart Disease (CHD) that causing more and more mortality and morbidity world wide. Identification of biomarkers for UA in the level of metabolomics is a better avenue to understand the inner mechanism of it. We carried out clinical epidemiology to collect plasmas of UA in-patients and controls. Metabolomics data are obtained by gas chromatography...
Text clustering is a hot and essential topic in data mining and information retrieval. This paper proposed a KP-FCM clustering method, which used the key phrases as text features and applied the Fuzzy c-means (FCM) as clustering algorithm. In this method, key phrases were extracted by an algorithm based on suffix array. Experimental results on two standard text clustering benchmark corpuses, OHSUMED...
Target recognition algorithm based on support vector machine of optimum parameters is put forward in this paper. Firstly, local surrounding-line integral bispectrum feature is extracted from the bispectrum of range profile of target. Secondly, parameter scope is obtained through experiment method, optimum parameters of support vector machine are gotten using genetic algorithm. Finally, support vector...
Blind source separation (BSS) can be used to separate mixed signals which is combined by the original data linearly, and obtain the source component which is statistically independent. The capacity of independent component analysis (ICA) is usually affected by the phase difference of the mixed signals. For this reason, an improved method called frequency domain BSS is proposed. By the properties of...
Knowledge element relation recognition is to mine intrinsic and hidden relations, i.e., preorder, analogy and illustration from knowledge element set, which can be used in knowledge organization and knowledge navigation system. This paper focuses on what information is employed to recognize knowledge element relations. First, a formal definition of knowledge element and the types of relation are given...
An approach is proposed for abnormal sections detection in video sequences. In this approach, firstly the histogram is selected to describe the color change in the section, and then the histograms of the frames selected from the section compose the histogram matrix. In order to improve the process efficiency, the principal components analysis (PCA) is used to reduce dimensions of the histogram matrix...
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